LDR | | 01684nam u200421 4500 |
001 | | 000000422770 |
005 | | 20190215170408 |
008 | | 181129s2016 |||||||||||||||||c||eng d |
020 | |
▼a 9780438086401 |
035 | |
▼a (MiAaPQ)AAI10246404 |
035 | |
▼a (MiAaPQ)okstate:14914 |
040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
082 | 0 |
▼a 581 |
100 | 1 |
▼a Espindola, Andres S. |
245 | 10 |
▼a Eukaryotic Plant Pathogen Detection Through High Throughput DNA/RNA Sequencing Data Analysis. |
260 | |
▼a [S.l.]:
▼b Oklahoma State University.,
▼c 2016. |
260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2016. |
300 | |
▼a 158 p. |
500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B. |
500 | |
▼a Adviser: Carla D. Garzon. |
502 | 1 |
▼a Thesis (Ph.D.)--Oklahoma State University, 2016. |
520 | |
▼a Plant pathogen detection is crucial for developing appropriate management techniques. A variety of tools are available for rapid plant pathogen detection. Most tools rely on unique features of the pathogen to detect its presence. Immunoassays re |
590 | |
▼a School code: 0664. |
650 | 4 |
▼a Plant pathology. |
650 | 4 |
▼a Bioinformatics. |
650 | 4 |
▼a Genetics. |
690 | |
▼a 0480 |
690 | |
▼a 0715 |
690 | |
▼a 0369 |
710 | 20 |
▼a Oklahoma State University.
▼b Plant Pathology (PhD). |
773 | 0 |
▼t Dissertation Abstracts International
▼g 79-11B(E). |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0664 |
791 | |
▼a Ph.D. |
792 | |
▼a 2016 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14996544
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
980 | |
▼a 201812
▼f 2019 |
990 | |
▼a ***1012033 |